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Accenture

Advises businesses and runs their technology

AI Delivery Tech Lead

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • Significant hands-on engineering experience building and running AI systems at enterprise production scale, including experience shipping production AI systems in regulated environments.
  • Strong engineering background with production experience in Python and similar programming languages across AI systems.
  • Proven track record architecting and delivering retrieval-augmented generation (RAG) pipelines, multi-agent systems, or large language model-based products at enterprise scale.
  • Deep hands-on experience with at least one major cloud AI platform: AWS Bedrock, Google Cloud Vertex AI, or Azure AI Studio.
  • Experience designing evaluation frameworks, red-teaming processes, and quality measurement for AI systems.
  • A portfolio or track record demonstrating production-deployed AI systems in regulated or enterprise environments.
  • Proven ability to lead engineering teams in agile, client-facing delivery contexts.
  • Deep practical experience with agentic frameworks such as LangGraph, LangChain, CrewAI, Agentforce, or similar; foundation model providers such as Claude Code, Codex, Gemini, OpenAI, or AWS Bedrock; vector databases such as Pinecone, Weaviate, LlamaIndex, or pgvector; cloud AI platforms such as AWS Bedrock, Google Cloud Vertex AI, or Azure AI Studio; and continuous integration and continuous delivery (CI/CD) for AI, including version-controlled prompts, automated testing, and deployment pipelines.
  • Experience with EU AI Act compliance, bias auditing, and model drift detection.
  • Strong technical leadership and engineering team management experience.
  • Ability to communicate complex technical topics confidently to senior client stakeholders.
  • Experience making and communicating architecture trade-offs under delivery pressure.
  • Understanding of commercial models and technical delivery economics in professional services.
  • Ability to lead within agile, collaborative consulting environments.
  • Experience in telecommunications or financial services.

Responsibilities

  • Contribute hands-on to contact center as a service (CCaaS) and AI design and build, delivering customer experience and contact platforms at scale.
  • Help clients build connected, always-on service models for their customers through CCaaS and AI innovation.
  • Transform customer journeys and service interactions using data, CCaaS platforms, and AI to create seamless and consistent experiences.
  • Build and lead delivery of RAG pipelines, multi-agent orchestration, and evaluation frameworks for enterprise-scale AI deployments.
  • Advise clients on AI architecture decisions, platform selection, and build-versus-buy trade-offs.
  • Define technical delivery approaches and infrastructure strategies.
  • Engage with client technical leadership at Principal and Director level.
  • Translate technical constraints into strategic recommendations.
  • Shape and deliver customer platform solutions that deepen clients’ understanding of how customers engage with their products and services.
  • Lead engineering teams across complex, multi-system agentic programs.
  • Set technical standards, quality frameworks, and architecture governance.
  • Ensure systems are designed for scalability, observability, and compliance.
  • Collaborate with Forward Deployed Engineers, Experience Designers, and Strategy leads.
  • Mentor engineers and grow technical capability within the practice.
  • Support sales, propositions, and go-to-market activity.
  • Contribute to thought leadership on production AI engineering and agentic delivery.
  • Spend time onsite with clients and partners as required to deliver services.

Desired Qualifications

  • Certifications in AWS, Google Cloud, Azure, or Anthropic AI platforms.
  • Open-source contributions to agentic or large language model tooling.
  • Contact center platform experience, such as Genesys, Sierra, Decagon, Parloa, PolyAI, NICE Cognigy, Agentforce Contact Centre, or Amazon Connect.
  • EU AI Act or AI governance certifications, or published guidance.
  • Experience in telecommunications, financial services, or the public sector.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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